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When we study the combinations of relative terms, from the most elementary forms of composition to the most complex patterns of correlation, we are considering the ways that these constraints, determinations, and informations, as imparted by relative terms, can be compounded in the formation of syntax.

When we study the combinations of relative terms, from the most elementary forms of composition to the most complex patterns of correlation, we are considering the ways that these constraints, determinations, and informations, as imparted by relative terms, can be compounded in the formation of syntax.

Let us go back and look more carefully at just how it happens that Peirce's jacent terms and subjacent indices manage to impart their respective measures of information about relations.

Let us go back and look more carefully at just how it happens that Peirce's adjacent terms and subjacent indices manage to impart their respective measures of information about relations.

I will begin with the two examples illustrated in Figures 1 and 2, where I have drawn in the corresponding lines of identity between the subjacent marks of reference #, $, %.

I will begin with the two examples illustrated in Figures&nbsp;1 and 2, where I have drawn in the corresponding lines of identity between the subjacent marks of reference:  <code>!, @, #</code>.

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o-------------------------------------------------o

o-------------------------------------------------o

|                                                |

|                                                |

|                                                |

|                                                |

|        'l'__#       #'s'__$   $w                |

|        'l'__!       !'s'__@   @w                |

|            o      o    o  o                |

|            o      o    o  o                |

|              \    /      \ /                  |

|              \    /      \ /                  |

|              \  /        o                  |

|              \  /        o                  |

|                \ /          $                   |

|                \ /          @                   |

|                o                              |

|                o                              |

|                #                               |

|                !                               |

|                                                |

|                                                |

|                                                |

|                                                |

Figure 1.  Lover of a Servant of a Woman

Figure 1.  Lover of a Servant of a Woman

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o-------------------------------------------------o

o-------------------------------------------------o

|                                                |

|                                                |

|                                                |

|                                                |

|        `g`__#__$   #'l'__%   %w  $h          |

|        `g`__!__@   !'l'__#   #w  @h          |

|            o  o    o    o  o    o            |

|            o  o    o    o  o    o            |

|              \  \  /      \ /    /            |

|              \  \  /      \ /    /            |

|              \  \/        o    /              |

|              \  \/        o    /              |

|                \ /\        %   /              |

|                \ /\        #   /              |

|                o  ------o------                |

|                o  ------o------                |

|                #       $                     |

|                !       @                     |

|                                                |

|                                                |

|                                                |

|                                                |

Figure 2.  Giver of a Horse to a Lover of a Woman

Figure 2.  Giver of a Horse to a Lover of a Woman

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One way to approach the problem of "information fusion" in Peirce's syntax is to soften the distinction between jacent terms and subjacent signs, and to treat the types of constraints that they separately signify more on a par with each other.

One way to approach the problem of "information fusion" in Peirce's syntax is to soften the distinction between jacent terms and subjacent signs, and to treat the types of constraints that they separately signify more on a par with each other.

For example, suppose that we are given the relations ''L''&nbsp;&sube;&nbsp;''X''&nbsp;&times;&nbsp;''Y'', ''M''&nbsp;&sube;&nbsp;''Y''&nbsp;&times;&nbsp;''Z''.  Table 3 and Figure 4 present a couple of ways of picturing the constraints that are involved in constructing the relational composition ''L''&nbsp;o&nbsp;''M''&nbsp;&sube;&nbsp;''X''&nbsp;&times;&nbsp;''Z''.

For example, suppose that we are given the relations ''L''&nbsp;&sube;&nbsp;''X''&nbsp;&times;&nbsp;''Y'', ''M''&nbsp;&sube;&nbsp;''Y''&nbsp;&times;&nbsp;''Z''.  Table 3 and Figure 4 present a couple of ways of picturing the constraints that are involved in constructing the relational composition ''L''&nbsp;o&nbsp;''M''&nbsp;&sube;&nbsp;''X''&nbsp;&times;&nbsp;''Z''.

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Table 3.  Relational Composition

Table 3.  Relational Composition

o---------o---------o---------o---------o

o---------o---------o---------o---------o

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The way to read Table 3 is to imagine that you are playing a game that involves placing tokens on the squares of a board that is marked in just this way.  The rules are that you have to place a single token on each marked square in the middle of the board in such a way that all of the indicated constraints are satisfied.  That is to say, you have to place a token whose denomination is a value in the set ''X'' on each of the squares marked "''X''", and similarly for the squares marked "''Y''" and "''Z''", meanwhile leaving all of the blank squares empty.  Furthermore, the tokens placed in each row and column have to obey the relational constraints that are indicated at the heads of the corresponding row and column.  Thus, the two tokens from ''X'' have to denominate the very same value from ''X'', and likewise for ''Y'' and ''Z'', while the pairs of tokens on the rows marked "''L''" and "''M''" are required to denote elements that are in the relations ''L'' and ''M'', respectively.  The upshot is that when just this much is done, that is, when the ''L'', ''M'', and !1! relations are satisfied, then the row marked "''L''&nbsp;o&nbsp;''M''" will automatically bear the tokens of a pair of elements in the composite relation ''L''&nbsp;o&nbsp;''M''.

The way to read Table 3 is to imagine that you are playing a game that involves placing tokens on the squares of a board that is marked in just this way.  The rules are that you have to place a single token on each marked square in the middle of the board in such a way that all of the indicated constraints are satisfied.  That is to say, you have to place a token whose denomination is a value in the set ''X'' on each of the squares marked "''X''", and similarly for the squares marked "''Y''" and "''Z''", meanwhile leaving all of the blank squares empty.  Furthermore, the tokens placed in each row and column have to obey the relational constraints that are indicated at the heads of the corresponding row and column.  Thus, the two tokens from ''X'' have to denominate the very same value from ''X'', and likewise for ''Y'' and ''Z'', while the pairs of tokens on the rows marked "''L''" and "''M''" are required to denote elements that are in the relations ''L'' and ''M'', respectively.  The upshot is that when just this much is done, that is, when the ''L'', ''M'', and !1! relations are satisfied, then the row marked "''L''&nbsp;o&nbsp;''M''" will automatically bear the tokens of a pair of elements in the composite relation ''L''&nbsp;o&nbsp;''M''.

Figure 4 shows a different way of viewing the same situation.

Figure 4 shows a different way of viewing the same situation.

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o-------------------------------------------------o

o-------------------------------------------------o

Figure 4.  Relational Composition

Figure 4.  Relational Composition

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===Commentary Note 10.3===

===Commentary Note 10.3===